Resumo:
Small-scale Argopuro Robusta coffee agroindustry has the potential to harm the environment in every supply chain activity. Even though the waste processing process has been carried out, this is still not enough to reduce the environmental impact. Performance measurement of Green Supply Chain Management (GSCM) in the business is complex because it considers environmental indicators and operational business as a whole. GSCM performance is also dynamic because the behavior of the supply chain system often changes over time. Therefore, it is necessary to develop a performance diagnosis model that has complex and dynamic characteristics through a system dynamic model. This research aims to diagnose and improve the GSCM performance index for currently and future using a system dynamic model. The scope of the model starts from harvesting coffee cherries to selling processed products. Research result shows that there are 13 performance indicators. The indicator values are then determined using the system dynamic model to obtain an index value of GSCM. The simulation results show that in 2023, the GSCM performance value will be 35.40, which is included in the good enough status, and 2035 the performance value increase by 54.8. To improve its performance, an optimistic scenario is used. This scenario is built by providing intervention to increase the percentage of waste processing by 90% for solid waste and 70% for liquid waste. Increase the number of pickup trucks by 4 units and reduce the motorcycle by 45 units to be more optimal and reduce the amount of emissions produced. The simulation results show that with that scenario the GSCM performance index was successfully increased to 68.2 (good status) in 2035.
